System and method for inverse treatment planning for radiation therapy

Abstract

Systems and methods are provided for determining a treatment plan for a radiation therapy system. The method includes dividing a three-dimensional volume of a patient into a grid of dose voxels, wherein at least a portion of said dose voxels are designated to belong to at least one target or to at least one critical structure. The method also includes modeling an ionizing radiation dose as delivered by a plurality of beamlets each having a beamlet fluence, to create a modeled radiation dose fluence map. The method also includes determining a voxel-based fluence map optimization (FMO) model for the modeled radiation dose a fluence map. The method also includes determining a conic optimization formulation for the FMO model to create a determined conic optimization solution and generating an optimized fluence map by updating the modeled radiation dose fluence map with the determined conic optimal fluence map.

1 . A method of determining a treatment plan for a radiation therapy system, comprising:
 determining a three-dimensional region of interest (ROI) in a subject containing a critical structure;   dividing the ROI into a grid of dose voxels;   modeling a radiation dose fluence map for the grid of dose voxels as delivered by the radiation therapy system with a plurality of beamlets to create a modeled radiation dose fluence map, each having a beamlet fluence;   determining a voxel-based fluence map optimization (FMO) model for the modeled radiation dose fluence map;   determining a conic optimization formulation for the FMO model to create a determined conic optimization solution;   generating an optimized fluence map by updating the modeled radiation dose fluence map with the determined conic optimization solution.   
     
     
         2 . The method of  claim 1 , wherein the conic optimization is a convex optimization that provides a globally optimal fluence map. 
     
     
         3 . The method of  claim 2 , wherein the voxel-based FMO model includes at least one of a quadratic, power, or exponential cone. 
     
     
         4 . The method of  claim 1 , wherein the conic optimization uses an interior point method and wherein generating the optimized fluence map includes determining a treatment plan with clinical objective and constraints for the ROI. 
     
     
         5 . The method of  claim 4 , wherein the interior point method includes at least one of a primal-dual or barrier interior point solver. 
     
     
         6 . The method of  claim 4 , wherein determining the conic optimization formulation includes applying convex functions selected as at least one of piece-wise linear functions, convex nonlinear functions, or piece-wise non-linear convex functions. 
     
     
         7 . The method of  claim 4 , wherein the interior point method includes determining the conic optimization solution in polynomial time. 
     
     
         8 . The method of  claim 4 , wherein the constraints include quadratic smoothing. 
     
     
         9 . The method of  claim 1 , wherein determining the conic optimization formulation includes determining an approximation that is conically representable for a clinical objective or constraint. 
     
     
         10 . The method of  claim 1 , wherein the ROI includes at least one of a radiation therapy target or a critical structure. 
     
     
         11 . A system for determining a treatment plan for a radiation therapy system, comprising:
 the radiation therapy system configured with adjustable beam shape settings to adjust a spatial dose delivered to a subject;   a computer system configured to:
 i) determine a three-dimensional region of interest (ROI) in the subject containing a critical structure; 
 ii) divide the ROI into a grid of dose voxels; 
 iii) model a radiation dose fluence map for the grid of dose voxels as delivered by the radiation therapy system with a plurality of beamlets to create a modeled radiation dose fluence map, each having a beamlet fluence; 
   iv) determine a voxel-based fluence map optimization (FMO) model for the modeled radiation dose fluence map;
 v) determine a conic optimization formulation for the FMO model to create a determined optimization solution; 
 vi) generate an optimized fluence map by updating the modeled radiation dose fluence map with the determined conic optimization solution; 
 vii) determine the beam shape settings for the optimized fluence map; and 
   a display configured to display the optimized fluence map.   
     
     
         12 . The system of  claim 11 , wherein the conic optimization is a convex optimization that provides a globally optimal fluence map. 
     
     
         13 . The system of  claim 12 , wherein the voxel-based FMO model includes at least one of a quadratic, power, or exponential cone. 
     
     
         14 . The system of  claim 11 , wherein the computer system is further configured to determine the conic optimization solution with an interior point method and wherein the computer system is further configured to determine treatment plan clinical objectives and constraints for the ROI and generate the optimized fluence map by using an interior point method. 
     
     
         15 . The system of  claim 14 , wherein the interior point method includes at least one of a primal-dual or barrier interior point solver. 
     
     
         16 . The system of  claim 14 , wherein the computer system is further configured to determine the conic optimization formulation by applying convex functions selected as at least one of piece-wise linear functions, convex nonlinear functions, or piece-wise non-linear convex functions. 
     
     
         17 . The system of  claim 14 , wherein the computer system is further configured to determine the conic optimization solution in polynomial time via interior point methods. 
     
     
         18 . The system of  claim 14 , wherein the constraints include quadratic smoothing. 
     
     
         19 . The system of  claim 11 , wherein the computer system is further configured to determine the conic optimization formulation by determining an approximation that is conically representable for a clinical objective or constraint. 
     
     
         20 . The system of  claim 11 , wherein the ROI includes at least one of a radiation therapy target or a critical structure. 
     
     
         21 . A method of determining a treatment plan for a radiation therapy system, the radiation therapy system comprising a radiation therapy unit, wherein a spatial dose delivered can be changed by adjusting beam shape settings, the method including steps comprising:
 dividing a three-dimensional volume of a patient into a grid of dose voxels, wherein at least a portion of said dose voxels are designated to belong to at least one target or to at least one critical structure;   modeling an ionizing radiation dose as delivered by a plurality of beamlets each having a beamlet fluence;   providing a quadratic, power and exponential cone voxel-based model for optimizing a fluence map, said fluence map defining said fluences for each of said plurality of beamlets; and   solving said model based on defined treatment plan clinical objectives and constraints for said at least one target and said at least one critical structure using an interior point algorithm to obtain a globally optimal fluence map.   
     
     
         22 . The method of  claim 21 , wherein the interior point method comprises a primal-dual or barrier interior point solver. 
     
     
         23 . The method of  claim 21 , wherein providing the conic formulation comprises applying convex functions selected from the group consisting of piece-wise linear functions, convex nonlinear functions, and piece-wise non-linear convex functions. 
     
     
         24 . The method of  claim 21 , wherein the interior point method ensures solving the conic form optimization problem in polynomial time. 
     
     
         25 . The method of  claim 21 , wherein the constraints include quadratic smoothing. 
     
     
         26 . The method of  claim 21 , further comprising controlling the radiation therapy unit at least based on the globally optimal fluence map.